Metadata-Version: 2.1
Name: rubber-ducky
Version: 1.1.3
Summary: AI Companion for Pair Programming
Home-page: https://github.com/ParthSareen/ducky
Author: Parth Sareen
Author-email: psareen@uwaterloo.ca
License: MIT
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: ollama

# rubber ducky
<p align="center">
    <img src="ducky_img.webp" alt="Ducky Image" width="200" height="200">
</p>

## tl;dr
- `pip install rubber-ducky`
- Install ollama
- `ollama pull codellama` (first time and then you can just have application in background)
- There are probably other dependencies which I forgot to put in setup.py sorry in advance.
- Run with `ducky <path>` or `ducky <question>`

## Dependencies

You will need Ollama installed on your machine. The model I use for this project is `codellama`. 

For the first installation you can run `ollama pull codellama` and it should pull the necessary binaries for you.

Ollama is also great because it'll spin up a server which can run in the background and can even do automatic model switching as long as you have it installed.

## Usage

Install through [pypi](https://pypi.org/project/rubber-ducky/):

`pip install rubber-ducky` .

### Simple run
`ducky`

or 

`ducky <question>`

or 

`ducky -f <path>`


### All options
`ducky --file <path> --prompt <prompt> --directory <directory> --chain --model <model>`

Where:
- `--prompt` or `-p`: Custom prompt to be used
- `--file` or `-f`: The file to be processed
- `--directory` or `-d`: The directory to be processed
- `--chain` or `-c`: Chain the output of the previous command to the next command
- `--model` or `-m`: The model to be used (default is "codellama")


## Example output
![Screenshot of ducky](image.png)
